Model Predictive Control for Multi-Class Traffic Flows
作者： Puspita Deo , Bart De Schutter , Andreas Hegyi
DOI: 10.3182/20090902-3-US-2007.0017
关键词: Traffic congestion reconstruction with Kerner's three-phase theory 、 Traffic flow 、 Macroscopic traffic flow model 、 Microscopic traffic flow model 、 Simulation 、 Model predictive control 、 Control theory 、 Traffic generation model 、 Benchmark (computing) 、 Computer science
摘要: Abstract In this paper we first present an extension of the macroscopic traffic flow model METANET to multi-class flows. The resulting takes into account differences between, e.g., fast vehicles (cars) and slow (trucks) including their possibly different free-flow speeds critical densities. Next, show how can be used in a model-based predictive control approach for coordinated integrated control. particular, use Model Predictive Control (MPC) coordinate various measures such as variable speed limits, ramp metering, etc. Using simple benchmark example from literature illustrate that by taking heterogeneous nature flows better performance obtained.
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